Structural health monitoring of offshore wind turbines using distributed acoustic sensing (DAS)

Abstract

AbstractThis paper presents the results of a first of its kind application and validation of fiber optic strain sensing for structural health monitoring of offshore wind turbines. A full-scale wind turbine was tested at the University of California, Berkeley’s shaking table. The test employed two Rayleigh-based Distributed Fiber Optic Sensing (DFOS) technologies to monitor dynamic strain profiles in a wind turbine that was subjected to strains representative of a typical offshore wind turbine environment. The two technologies used were Optical Frequency-Domain Reflectometry (OFDR), which can measure strain (tens of meters), and Phase-sensitive Optical Time-Domain Reflectometry ($$\phi$$ ϕ -OTDR), a technology used in DAS, which can measure strain over large distances (several kilometers). Target dynamic strain profiles were determined prior to testing using a prototype floating offshore wind turbine simulated in the computational software, OpenFAST. Fiber optic cables were installed onto a wind turbine tower in different orientations to capture global tower deformations and local strain. First, a quasi-static bend test of the entire tower was conducted to calibrate the sensing techniques. Second, the tower was mounted on a six degree of freedom shake table and was subjected to multi-directional (translational and rotational) shaking to induce dynamic strain profiles similar to offshore conditions. Different configurations of loose bolts at the turbine flange connections were also tested to evaluate the proposed sensing approach. The results show good agreement between $$\phi$$ ϕ -OTDR and OFDR measurements and show that the technologies captured both local and global structural phenomena; the effect of loose bolts on strain response was readily identified. In addition, numerous lessons on effective sensing installation techniques were identified. $$\phi$$ ϕ -OTDR’s ability to accurately capture dynamic strain over large distances makes it a promising candidate for Structural Health Monitoring (SHM) of large civil systems, though mitigating vibration noise is essential to measure small strains accurately.